Metaheuristics algorithm and optimization of engineering and complex systems:
"In the field of engineering, optimization and decision-making have become pivotal concerns. The ever-increasing demand for data processing has given rise to issues such as extended processing times and escalated memory utilization, posing formidable obstacles across various engineering domains...
Gespeichert in:
| Weitere Verfasser: | , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
2024.
|
| Schlagworte: | |
| Online-Zugang: | DE-862 DE-863 |
| Zusammenfassung: | "In the field of engineering, optimization and decision-making have become pivotal concerns. The ever-increasing demand for data processing has given rise to issues such as extended processing times and escalated memory utilization, posing formidable obstacles across various engineering domains. Problems persist, requiring not only solutions but advancements beyond existing best practices. Creating and implementing novel heuristic algorithms is a time-intensive process, yet the imperative to do so remains strong, driven by the potential to significantly lower computational costs even with marginal improvements. This book, titled Metaheuristics Algorithm and Optimization of Engineering and Complex Systems, is a beacon of innovation in this context. It examines the critical need for inventive algorithmic solutions, exploring hyperheuristic approaches that offer solutions such as automating search spaces through integrated heuristics.Designed to cater to a broad audience, this book is a valuable resource for both novice and experienced dynamic optimization practitioners. By addressing the spectrum of theory and practice, as well as discrete versus continuous dynamic optimization, it becomes an indispensable reference in a captivating and emerging field. With a deliberate focus on inclusivity, the book is poised to benefit anyone with an interest in staying abreast of the latest developments in dynamic optimization."-- |
| Beschreibung: | 25 PDFs (423 Seiten) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9798369333150 |
| Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
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| 245 | 0 | 0 | |a Metaheuristics algorithm and optimization of engineering and complex systems |c Thanigaivelan R., Suchithra M., Kaliappan S., Mothilal T., editors. |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) |b IGI Global |c 2024. | |
| 300 | |a 25 PDFs (423 Seiten) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Chapter 1. An application of deep neural network using GNS for solving complex fluid dynamics problems -- Chapter 2. An integrated approach of particle swarm optimization and grey relational analysis in multi-response optimization of fused deposition modeling -- Chapter 3. A novel approach for optimizing wire electric discharge machining of Mg-Cu-RE-Zr alloy using machine learning algorithm -- Chapter 4. Optimizing precision machining of inconel alloy through hybrid taguchi and meta-heuristic GA method in electrochemical machining -- Chapter 5. Metaheuristic techniques-based optimizing laser welding parameters for copper-aluminum alloys -- Chapter 6. Meta-heuristic optimization for enhancing the thermal performance of solar energy devices -- Chapter 7. Optimizing shot peening machines for compact components -- Chapter 8. A comparative analysis of meta-heuristic algorithms for optimal configuration of hybrid renewable energy systems for remote villages -- Chapter 9. A novel machine learning-based optimizing multipass milling parameters for enhanced manufacturing efficiency -- Chapter 10. An advanced hybrid algorithm (haDEPSO) for engineering design optimization integrating novel strategies for enhanced performance -- Chapter 11. An artificial neural network with a metaheuristic basis for plastic limit frames analysis -- Chapter 12. An extensive investigation of meta-heuristics algorithms for optimization problems -- Chapter 13. Compare the performance of meta-heuristics algorithm: a review -- Chapter 14. Efficient design and optimization of high-speed electronic system interconnects using machine learning applications -- Chapter 15. Enhancement of system performance using pesche scheduling algorithm on multiprocessors -- Chapter 16. Enhancing operational cost savings in electric utilities on global optimization in power system planning and operation -- Chapter 17. Enhancing photovoltaic system performance using PSO for maximum power point tracking and DC-bus voltage regulation in grid-connected PV systems. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | 3 | |a "In the field of engineering, optimization and decision-making have become pivotal concerns. The ever-increasing demand for data processing has given rise to issues such as extended processing times and escalated memory utilization, posing formidable obstacles across various engineering domains. Problems persist, requiring not only solutions but advancements beyond existing best practices. Creating and implementing novel heuristic algorithms is a time-intensive process, yet the imperative to do so remains strong, driven by the potential to significantly lower computational costs even with marginal improvements. This book, titled Metaheuristics Algorithm and Optimization of Engineering and Complex Systems, is a beacon of innovation in this context. It examines the critical need for inventive algorithmic solutions, exploring hyperheuristic approaches that offer solutions such as automating search spaces through integrated heuristics.Designed to cater to a broad audience, this book is a valuable resource for both novice and experienced dynamic optimization practitioners. By addressing the spectrum of theory and practice, as well as discrete versus continuous dynamic optimization, it becomes an indispensable reference in a captivating and emerging field. With a deliberate focus on inclusivity, the book is poised to benefit anyone with an interest in staying abreast of the latest developments in dynamic optimization."-- |c Provided by publisher. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 08/12/2024). | ||
| 650 | 0 | |a Algorithms. | |
| 650 | 0 | |a Artificial intelligence |x Industrial applications. | |
| 650 | 0 | |a Engineering |x Data processing. | |
| 650 | 0 | |a Machine learning. | |
| 653 | |a Electrochemical Meta-Heuristic Technique-Based Parametric Optimization. | ||
| 653 | |a Electrospark Meta-Heuristic Technique-Based Parametric Optimization. | ||
| 653 | |a Hybrid Meta-Heuristic Algorithm for Process Optimization. | ||
| 653 | |a Laser Meta-Heuristic Technique-Based Parametric Optimization. | ||
| 653 | |a Machine Learning in IIOT. | ||
| 653 | |a Machining Operation. | ||
| 653 | |a Meta-Heuristic Algorithm for Computer Communications. | ||
| 653 | |a Meta-Heuristic Algorithm-Based Power Distribution System. | ||
| 653 | |a Meta-Heuristic and Machine Learning Modelling. | ||
| 653 | |a Meta-Heuristic and Machine Learning Optimization. | ||
| 653 | |a Meta-Heuristics Applications in Power Systems Trends. | ||
| 653 | |a Meta-Heuristics Approach in Cloud Computing. | ||
| 653 | |a Milling Operation. | ||
| 653 | |a Optimal Sizing of Hybrid Renewable Energy System. | ||
| 653 | |a Thermal Performance of Solar Energy Devices Optimization. | ||
| 655 | 4 | |a Electronic books. | |
| 700 | 1 | |a M., Suchithra |e editor. | |
| 700 | 1 | |a R., Thanigaivelan |e editor. | |
| 700 | 1 | |a S., Kaliappan |e editor. | |
| 700 | 1 | |a T., Mothilal |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
| 776 | 0 | 8 | |i Print version: |z 9798369333143 |
| 966 | 4 | 0 | |l DE-862 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-3314-3 |3 Volltext |
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| 912 | |a ZDB-98-IGB | ||
| 049 | |a DE-862 | ||
| 049 | |a DE-863 | ||
Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-98-IGB-00335467 |
|---|---|
| _version_ | 1826942603163074560 |
| adam_text | |
| any_adam_object | |
| author2 | M., Suchithra R., Thanigaivelan S., Kaliappan T., Mothilal |
| author2_role | edt edt edt edt |
| author2_variant | s m sm t r tr k s ks m t mt |
| author_facet | M., Suchithra R., Thanigaivelan S., Kaliappan T., Mothilal |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | T - Technology |
| callnumber-label | TA347 |
| callnumber-raw | TA347.A78 M48 2024e |
| callnumber-search | TA347.A78 M48 2024e |
| callnumber-sort | TA 3347 A78 M48 42024E |
| callnumber-subject | TA - General and Civil Engineering |
| collection | ZDB-98-IGB |
| contents | Chapter 1. An application of deep neural network using GNS for solving complex fluid dynamics problems -- Chapter 2. An integrated approach of particle swarm optimization and grey relational analysis in multi-response optimization of fused deposition modeling -- Chapter 3. A novel approach for optimizing wire electric discharge machining of Mg-Cu-RE-Zr alloy using machine learning algorithm -- Chapter 4. Optimizing precision machining of inconel alloy through hybrid taguchi and meta-heuristic GA method in electrochemical machining -- Chapter 5. Metaheuristic techniques-based optimizing laser welding parameters for copper-aluminum alloys -- Chapter 6. Meta-heuristic optimization for enhancing the thermal performance of solar energy devices -- Chapter 7. Optimizing shot peening machines for compact components -- Chapter 8. A comparative analysis of meta-heuristic algorithms for optimal configuration of hybrid renewable energy systems for remote villages -- Chapter 9. A novel machine learning-based optimizing multipass milling parameters for enhanced manufacturing efficiency -- Chapter 10. An advanced hybrid algorithm (haDEPSO) for engineering design optimization integrating novel strategies for enhanced performance -- Chapter 11. An artificial neural network with a metaheuristic basis for plastic limit frames analysis -- Chapter 12. An extensive investigation of meta-heuristics algorithms for optimization problems -- Chapter 13. Compare the performance of meta-heuristics algorithm: a review -- Chapter 14. Efficient design and optimization of high-speed electronic system interconnects using machine learning applications -- Chapter 15. Enhancement of system performance using pesche scheduling algorithm on multiprocessors -- Chapter 16. Enhancing operational cost savings in electric utilities on global optimization in power system planning and operation -- Chapter 17. Enhancing photovoltaic system performance using PSO for maximum power point tracking and DC-bus voltage regulation in grid-connected PV systems. |
| ctrlnum | (CaBNVSL)slc00006585 (OCoLC)1452677617 |
| dewey-full | 006.3 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3 |
| dewey-search | 006.3 |
| dewey-sort | 16.3 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
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| genre | Electronic books. |
| genre_facet | Electronic books. |
| id | ZDB-98-IGB-00335467 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-18T14:30:38Z |
| institution | BVB |
| isbn | 9798369333150 |
| language | English |
| oclc_num | 1452677617 |
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| owner_facet | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| physical | 25 PDFs (423 Seiten) Also available in print. |
| psigel | ZDB-98-IGB FWS_PDA_IGB ZDB-98-IGB |
| publishDate | 2024 |
| publishDateSearch | 2024 |
| publishDateSort | 2024 |
| publisher | IGI Global |
| record_format | marc |
| spelling | Metaheuristics algorithm and optimization of engineering and complex systems Thanigaivelan R., Suchithra M., Kaliappan S., Mothilal T., editors. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) IGI Global 2024. 25 PDFs (423 Seiten) text rdacontent electronic isbdmedia online resource rdacarrier Includes bibliographical references and index. Chapter 1. An application of deep neural network using GNS for solving complex fluid dynamics problems -- Chapter 2. An integrated approach of particle swarm optimization and grey relational analysis in multi-response optimization of fused deposition modeling -- Chapter 3. A novel approach for optimizing wire electric discharge machining of Mg-Cu-RE-Zr alloy using machine learning algorithm -- Chapter 4. Optimizing precision machining of inconel alloy through hybrid taguchi and meta-heuristic GA method in electrochemical machining -- Chapter 5. Metaheuristic techniques-based optimizing laser welding parameters for copper-aluminum alloys -- Chapter 6. Meta-heuristic optimization for enhancing the thermal performance of solar energy devices -- Chapter 7. Optimizing shot peening machines for compact components -- Chapter 8. A comparative analysis of meta-heuristic algorithms for optimal configuration of hybrid renewable energy systems for remote villages -- Chapter 9. A novel machine learning-based optimizing multipass milling parameters for enhanced manufacturing efficiency -- Chapter 10. An advanced hybrid algorithm (haDEPSO) for engineering design optimization integrating novel strategies for enhanced performance -- Chapter 11. An artificial neural network with a metaheuristic basis for plastic limit frames analysis -- Chapter 12. An extensive investigation of meta-heuristics algorithms for optimization problems -- Chapter 13. Compare the performance of meta-heuristics algorithm: a review -- Chapter 14. Efficient design and optimization of high-speed electronic system interconnects using machine learning applications -- Chapter 15. Enhancement of system performance using pesche scheduling algorithm on multiprocessors -- Chapter 16. Enhancing operational cost savings in electric utilities on global optimization in power system planning and operation -- Chapter 17. Enhancing photovoltaic system performance using PSO for maximum power point tracking and DC-bus voltage regulation in grid-connected PV systems. Restricted to subscribers or individual electronic text purchasers. "In the field of engineering, optimization and decision-making have become pivotal concerns. The ever-increasing demand for data processing has given rise to issues such as extended processing times and escalated memory utilization, posing formidable obstacles across various engineering domains. Problems persist, requiring not only solutions but advancements beyond existing best practices. Creating and implementing novel heuristic algorithms is a time-intensive process, yet the imperative to do so remains strong, driven by the potential to significantly lower computational costs even with marginal improvements. This book, titled Metaheuristics Algorithm and Optimization of Engineering and Complex Systems, is a beacon of innovation in this context. It examines the critical need for inventive algorithmic solutions, exploring hyperheuristic approaches that offer solutions such as automating search spaces through integrated heuristics.Designed to cater to a broad audience, this book is a valuable resource for both novice and experienced dynamic optimization practitioners. By addressing the spectrum of theory and practice, as well as discrete versus continuous dynamic optimization, it becomes an indispensable reference in a captivating and emerging field. With a deliberate focus on inclusivity, the book is poised to benefit anyone with an interest in staying abreast of the latest developments in dynamic optimization."-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 08/12/2024). Algorithms. Artificial intelligence Industrial applications. Engineering Data processing. Machine learning. Electrochemical Meta-Heuristic Technique-Based Parametric Optimization. Electrospark Meta-Heuristic Technique-Based Parametric Optimization. Hybrid Meta-Heuristic Algorithm for Process Optimization. Laser Meta-Heuristic Technique-Based Parametric Optimization. Machine Learning in IIOT. Machining Operation. Meta-Heuristic Algorithm for Computer Communications. Meta-Heuristic Algorithm-Based Power Distribution System. Meta-Heuristic and Machine Learning Modelling. Meta-Heuristic and Machine Learning Optimization. Meta-Heuristics Applications in Power Systems Trends. Meta-Heuristics Approach in Cloud Computing. Milling Operation. Optimal Sizing of Hybrid Renewable Energy System. Thermal Performance of Solar Energy Devices Optimization. Electronic books. M., Suchithra editor. R., Thanigaivelan editor. S., Kaliappan editor. T., Mothilal editor. IGI Global, publisher. Print version: 9798369333143 |
| spellingShingle | Metaheuristics algorithm and optimization of engineering and complex systems Chapter 1. An application of deep neural network using GNS for solving complex fluid dynamics problems -- Chapter 2. An integrated approach of particle swarm optimization and grey relational analysis in multi-response optimization of fused deposition modeling -- Chapter 3. A novel approach for optimizing wire electric discharge machining of Mg-Cu-RE-Zr alloy using machine learning algorithm -- Chapter 4. Optimizing precision machining of inconel alloy through hybrid taguchi and meta-heuristic GA method in electrochemical machining -- Chapter 5. Metaheuristic techniques-based optimizing laser welding parameters for copper-aluminum alloys -- Chapter 6. Meta-heuristic optimization for enhancing the thermal performance of solar energy devices -- Chapter 7. Optimizing shot peening machines for compact components -- Chapter 8. A comparative analysis of meta-heuristic algorithms for optimal configuration of hybrid renewable energy systems for remote villages -- Chapter 9. A novel machine learning-based optimizing multipass milling parameters for enhanced manufacturing efficiency -- Chapter 10. An advanced hybrid algorithm (haDEPSO) for engineering design optimization integrating novel strategies for enhanced performance -- Chapter 11. An artificial neural network with a metaheuristic basis for plastic limit frames analysis -- Chapter 12. An extensive investigation of meta-heuristics algorithms for optimization problems -- Chapter 13. Compare the performance of meta-heuristics algorithm: a review -- Chapter 14. Efficient design and optimization of high-speed electronic system interconnects using machine learning applications -- Chapter 15. Enhancement of system performance using pesche scheduling algorithm on multiprocessors -- Chapter 16. Enhancing operational cost savings in electric utilities on global optimization in power system planning and operation -- Chapter 17. Enhancing photovoltaic system performance using PSO for maximum power point tracking and DC-bus voltage regulation in grid-connected PV systems. Algorithms. Artificial intelligence Industrial applications. Engineering Data processing. Machine learning. |
| title | Metaheuristics algorithm and optimization of engineering and complex systems |
| title_auth | Metaheuristics algorithm and optimization of engineering and complex systems |
| title_exact_search | Metaheuristics algorithm and optimization of engineering and complex systems |
| title_full | Metaheuristics algorithm and optimization of engineering and complex systems Thanigaivelan R., Suchithra M., Kaliappan S., Mothilal T., editors. |
| title_fullStr | Metaheuristics algorithm and optimization of engineering and complex systems Thanigaivelan R., Suchithra M., Kaliappan S., Mothilal T., editors. |
| title_full_unstemmed | Metaheuristics algorithm and optimization of engineering and complex systems Thanigaivelan R., Suchithra M., Kaliappan S., Mothilal T., editors. |
| title_short | Metaheuristics algorithm and optimization of engineering and complex systems |
| title_sort | metaheuristics algorithm and optimization of engineering and complex systems |
| topic | Algorithms. Artificial intelligence Industrial applications. Engineering Data processing. Machine learning. |
| topic_facet | Algorithms. Artificial intelligence Industrial applications. Engineering Data processing. Machine learning. Electronic books. |
| work_keys_str_mv | AT msuchithra metaheuristicsalgorithmandoptimizationofengineeringandcomplexsystems AT rthanigaivelan metaheuristicsalgorithmandoptimizationofengineeringandcomplexsystems AT skaliappan metaheuristicsalgorithmandoptimizationofengineeringandcomplexsystems AT tmothilal metaheuristicsalgorithmandoptimizationofengineeringandcomplexsystems AT igiglobal metaheuristicsalgorithmandoptimizationofengineeringandcomplexsystems |